The Silicon &Artificial Intelligence (SAI) lab focuses on exploring the field where deep learning and hardware architecture intersect. Our primary goal is to co-optimize AI algorithms and the underlying hardware architecture to enhance the implementation of AI. Additionally, we leverage AI as a powerful tool to streamline the hardware design process.


If you are interested in working with us, please send your CV to

Ph.D. Students

I am hiring multiple PhD students starting Fall 2024 to work on the following two areas:

AI algorithm:

  • Efficient DNN inference/finetuning, parameter efficient finetuning.
  • AI privacy
  • Multi-agent reinforcement learning

AI hardware:

  • AI accelerator for DNN training and inference.
  • In(Near)-mem computing


If you are NYU students and interested in working with me, please contact me directly:)

Yihao Wang (2023-)

Zhenyuan Dong (2023-)


I am always taking undergrads/interns (can be remote) to work on the above two areas:), each intern will be supervised by me directly, most of them will end up with a top conference submission by the end of the internship.


Yixuan Luo (2023.07-2023.11): One paper was submitted to CVPR'24

Chao Gao (2023.07-): One paper was submitted to CVPR'24

Tianhua Xia (2023.07-2023.11): One paper was submitted to DAC'24

Wenshuo Peng (2023.07-): One paper is submitted to NAACL'24